Sketch-Based Tree Modeling Using Markov Random Field

In this paper, we describe a new system for converting a user's freehand sketch of a tree into a full 3D model that is both complex and realistic-looking. Our system does this by probabilistic optimization based on parameters obtained from a database of tree models. The best matching model is selected by comparing its 2D projections with the sketch. Branch interaction is modeled by a Markov random field, subject to the constraint of 3D projection to sketch. Our system then uses the notion of self-similarity to add new branches before finally populating all branches with leaves of the user's choice. We show a variety of natural-looking tree models generated from freehand sketches with only a few strokes.